import cv2 as cv

cvNet = cv.dnn.readNetFromTensorflow('data\model.pb', 'data\graph.pbtxt')

img = cv.imread('img\IMG_kitti_0011_000187.png')
rows = img.shape[0]
cols = img.shape[1]
cvNet.setInput(cv.dnn.blobFromImage(img, size=(300, 300), swapRB=True, crop=False))
cvOut = cvNet.forward()

for detection in cvOut[0,0,:,:]:
    score = float(detection[2])
    if score > 0.3:
        left = detection[3] * cols
        top = detection[4] * rows
        right = detection[5] * cols
        bottom = detection[6] * rows
        cv.rectangle(img, (int(left), int(top)), (int(right), int(bottom)), (23, 230, 210), thickness=2)
        cv.putText(img, str(score), (int(right), int(bottom)), cv.FONT_HERSHEY_SIMPLEX, 1, (23, 230, 210), 2)

cv.imshow('img', img)
cv.waitKey()